Bibliographic record
Abstract
A newly established multiplexed network protocol - QUIC, which is based on User Datagram Protocol (UDP), has emerged in recent years and gained a large share of Internet traffic quickly. Initially proposed by Google, the goal of QUIC is to achieve a higher Internet communication performance and eventually replace the Transmission Control Protocol (TCP) + Transport Layer Security (TLS) + HTTP/2 architecture. In particular, the 3rdversion of the Hypertext Transfer Protocol - HTTP/3.0 is built on top of QUIC. A good number of research papers have been published recently to evaluate the performance and security of the QUIC protocol. In this paper, we conduct a comprehensive survey on the QUIC security issues and analyze its future research directions regarding security prospective. We investigate several topics including the QUIC protocol structure, QUIC security model, security issues related to QUIC protocol, and future research directions on QUIC Security. To the best of our knowledge, it is the one of first surveys that focus on the security of the QUIC protocol.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.011 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".